Probability and Statistics in Complex Systems: Genomics, Networks, and Financial Engineering, September 1, 2003 - June 30, 2004

Organizers:

Michael A. Newton
Department of Statistics and Department of Biostatistics and Medical Informatics
University of Wisconsin-Madison
newton@stat.wisc.edu
http://www.stat.wisc.edu/~newton/

and

Giovanni Parmigiani
The Sidney Kimmel Comprehensive Cancer Center and Department of Biostatistics
Johns Hopkins University
gp@jhu.edu
http://astor.som.jhmi.edu/~gp

Technological advances and resources created by genome sequencing projects have enabled biomedical scientists to measure precisely and simultaneously the abundance of thousands of molecular targets in living systems. The effect has been dramatic, not only for biology, where now the cellular role for all genes may be investigated, or for medicine, where new drug targets may be found and new approaches discovered for characterizing and treating complex diseases; the effect has also been dramatic for the mathematical and computational sciences. To assess a major component of this activity, the IMA workshop will focus on statistical issues in the study of gene expression both at the level of RNA transcripts and proteomics. Leading investigators will describe current research and future challenges in this area. The workshop format entails three lectures per day and extensive opportunity for fruitful discussion and interaction.

Various microarray technologies for measuring RNA transcript abundance have created some challenging statistical problems. There are many sources of variation in a typical experiment and these can be accounted for using statistical design and analysis-of-variance methodology; but careful attention has to be given to the high-dimensionality and complicated interactions. Statistical methods invoked early in the data analysis pipeline can remove systematic errors and improve subsequent inferences. Robust statistical methods are important to account for influential observations that may be hidden in massive data sets. A wide range of supervised and unsupervised learning methods have been considered to better organize data, be it to infer coordinated patterns of gene expression, to discover molecular signatures of disease subtypes, or to derive various predictions. Related efforts aim to reconstruct regulatory networks from large sets of expression data. Theoretical problems arise in statistical inference when attempting to address thousands of gene-specific hypotheses at once, such as the problem to bound the rate of false detections of differential expression. Further, research in statistical computing concerns infrastructure to enable efficient and flexible calculations with large expression data sets. The workshop will consider these and other pressing problems generated in current research.

WORKSHOP SCHEDULE
Monday Tuesday Wednesday Thursday Friday
MONDAY, SEPTEMBER 29 All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted.
8:30	Coffee and Registration	Reception Room EE/CS 3-176
9:15	Douglas N. Arnold, Scot Adams, and Organizers	Welcome and Introduction
9:30	Terry Speed WEHI, Melbourne and UC Berkeley	Mining a Tandem Mass Spectrometry Database to Determine the Trends and Global Factors Influencing Peptide Fragmentation Slides:   html    pdf    ps    ppt
10:20	Discussion
10:30	Coffee Break	Reception Room EE/CS 3-176
11:00	David Allison University of Alabama at Birmingham	Applying High-Dimensional Approaches to Microarray Research Slides:   pdf
11:25	Discussion
11:30	David M. Rocke University of California, Davis	Measurement Errors and Data Transformation for Gene Expression Data, Proteomics and Metabolomics Data Slides:   pdf
11:55	Discussion
12:00	Lunch Break
1:30	Atul Butte, MD Children's Hospital Informatics Program and Harvard Medical School	Integrative Genomics and its Implications for Clinical Research and Care: What Are the Real Issues Beyond Analysis? Slides:   pdf
2:20	Discussion
2:30	Coffee Break	Reception Room EE/CS 3-176
3:00	SECOND CHANCES, i.e., speakers of the day respond to further questions, suggestions, re-frame their main points, look toward future directions.
3:30	Group Photo here
3:40	IMA Tea and more (with POSTER SESSION) 400 Lind Hall Shilpi Arora Princess Margaret Hospital/Ontario Cancer Institute, Toronto Gene Expression Profiling of Human Oral Cancer Using cDNA Microarrays Karla Ballman Mayo Clinic Fast Loess for Normalizing Microarray Data Joseph Beyene University of Toronto A Spectral Clustering Method for Microarray Data David B. Dahl University of Wisconsin - Madison Modeling Differential Gene Expression using a Dirichlet Process Mixture Model Shmuel Friedland IMA A Theoretical Framework For Reconstructing Missing Data in Genome - Wide Matrix Rebecka Jornsten Rutgers University Data Depth Based Clustering and Classification Boris Khots/ Dmitriy Khots Iowa, USA Why Infinite-dimensional topological groups may work for Genetics data Slides:   html    pdf    ps    ppt Pim (W.W.) Kuurman Animal Sciences Group, Wageningen UR, The Netherlands Procedure for standardisation and normalisation of cDNA microarrays Poster file:   pool.pdf Talk handout:  EAAPpresentatie.pdf EAAPpresentatie.doc Wentian Li The Robert S Boas Center for Genomics and Human Genetics, North Shore LIJ Research Institute Extreme-Value Distribution Based Gene Selection Criteria for Discriminant Microarray Data Analysis Using Logistic Regression Adriana Lopez University of Pittsburgh Cancer tumor classification using gene expression data Ann L. Oberg The Mayo Clinic Joint Estimation of Calibration and Expression for High-density Oligonucleotide Arrays Lídia Rejtö University of Delaware Bayesian Analysis of Microarrays Hae-Hiang Song The Catholic University of Korea Statistical Inference Methods for Detecting Altered Gene Associations Mahlet G. Tadesse Texas A&M University A Bayesian Method for Class Discovery and Gene Selection Achim Tresch Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven Germany Using Text Mining Networks for the Context Specific Interpretation of Expression Data Kenny Q. Ye SUNY at Stony Brook Pooling or not pooling in microarray experiments - an experimental design point of view Ming Yuan University of Wisconsin, Madison Hidden Markov Models for Microarray Time Course Data in Multiple Biological Conditions
TUESDAY, SEPTEMBER 30 All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted.
9:00	Coffee	Reception Room EE/CS 3-176
9:30	Sandrine Dudoit University of California, Berkeley	Loss-based estimation methodology with cross-validation: Prediction of clinical outcomes using microarray data Slides:   pdf
10:20	Discussion
10:30	Coffee Break	Reception Room EE/CS 3-176
11:00	Hongzhe Li UC Davis School of Medicine	Microarray Time Course Gene Expresssion Studies: Some Problems and Statistical Methods Slides:  pdf
11:25	Discussion
11:30	Kathleen Kerr University of Washington	Empirical Evaluation of Methodologies for Microarray Data Analysis, With Some Thoughts on Statistical Implications Slides:   pdf
11:55	Discussion
12:00	Lunch Break
1:30	John Quackenbush The Institute for Genomic Research	Beyond Significance: Integrating Diverse Data Types to Extract Biological Meaning from Microarrays Slides:   pdf
2:20	Discussion
2:30	Coffee Break	Reception Room EE/CS 3-176
3:00	SECOND CHANCES, i.e., speakers of the day respond to further questions, suggestions, re-frame their main points, look toward future directions.
4:00	Soccer match (weather permitting) Photo	Van Cleve Park, 15th Ave and Como Ave
WEDNESDAY, OCTOBER 1 All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted.
9:00	Coffee	Reception Room EE/CS 3-176
9:30	Keith Baggerly M.D. Anderson Cancer Center	The Analysis of Proteomics Spectra from Serum Samples Slides:   pdf
10:20	Discussion
10:30	Coffee Break	Reception Room EE/CS 3-176
11:00	Yee Hwa (Jean) Yang University of California, San Francisco	Comparing Normalization Methods Based on Splice Array Experiments Slides:   pdf
11:25	Discussion
11:30	Wolfgang Huber German Cancer Research Center	Interpretation and Transformation of Microarray Data Slides:   html    pdf    ps    ppt
11:55	Discussion
12:00	Lunch Break
1:30	Peter J. Munson DCB, CIT, NIH, DHHS	Mining a Gene Expression Database
2:20	Discussion
2:30	Coffee Break	Reception Room EE/CS 3-176
3:00	SECOND CHANCES, i.e., speakers of the day respond to further questions, suggestions, re-frame their main points, look toward future directions.
3:30	Mississippi walk (weather permitting)	Begins and ends at EE/CS 3-180
THURSDAY, OCTOBER 2 All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted.
9:00	Coffee	Reception Room EE/CS 3-176
9:30	Geoff McLachlan University of Queensland	Classification of Microarray Gene-Expression Data Slides:   html    pdf    ps    ppt
10:20	Discussion
10:30	Coffee Break	Reception Room EE/CS 3-176
11:00	Christina Kendziorski University of Wisconsin - Madison	Hidden Markov Models for Microarray Time Course Data in Multiple Biological Conditions Slides:    html    pdf    ps    ppt
11:25	Discussion
11:30	Michael Ochs Fox-Chase Cancer Center	Encoding Prior Biological Knowledge in Functional Genomics Analysis Slides:   html    pdf    ps    ppt
11:55	Discussion
12:00	Lunch Break
1:30	Marco F. Ramoni Harvard Medical School	Bayesian Methods for Microarray Data Analysis Slides:   pdf
2:20	Discussion
2:30	Coffee Break	Reception Room EE/CS 3-176
3:00	SECOND CHANCES, i.e., speakers of the day respond to further questions, suggestions, re-frame their main points, look toward future directions.
6:00	Workshop Dinner	Jewel of India 1427 Washington Avenue
FRIDAY, OCTOBER 3 NOTE THE ABBREVIATED SCHEDULE FOR FRIDAY; FIRST TALK AT 9:10 All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted.
9:00	Coffee	Reception Room EE/CS 3-176
9:10	Mark van der Laan University of California, Berkeley	Prediction of Survival Slides:   pdf
10:00	Discussion
10:10	Coffee Break	Reception Room EE/CS 3-176
10:20	Terry M. Therneau Mayo Clinic	Joint calibration and fitting of microarray data Slides:   pdf   ps Figure:   description    pdf    ps
11:10	Discussion
11:20	Coffee Break	Reception Room EE/CS 3-176
11:30	SECOND CHANCES, i.e., speakers of the day respond to further questions, suggestions, re-frame their main points, look toward future directions.
11:50	Concluding Remarks by Organizers
12:00	End of Workshop

LIST OF CONFIRMED PARTICIPANTS

NAME	DEPARTMENT	AFFILIATION
Edgar Acuna	Department of Mathematics	University of Puerto Rico
Scot Adams	Institute for Mathematics and its Applications	University of Minnesota
Pujya Agarwal	Laboratory Medicine and Pathology	University of Minnesota
Soohan Ahn	Department of Statistics	Seoul National University
David Allison	Department of Biostatistics	University of Alabama at Birmingham
Yusuf Altundas	Institute for Mathematics and its Applications	Schlumberger-Doll
Greg Anderson	School of Mathematics	University of Minnesota
Douglas Arnold	Institute for Mathematics and its Applications	University of Minnesota
Donald Aronson	Institute for Mathematics and its Applications	University of Minnesota
Shilpi Arora	Cancer Institute	Princess Margaret Hospital
Gerard Awanou	Institute for Mathematics and its Applications	University of Minnesota
Mary Baddorf	Department of Molecular Veterinary Biosciences	University of Minnesota
Keith Baggerly	M. D. Anderson Cancer Center	University of Texas at Austin
Karen Ball	Institute for Mathematics and its Applications	University of Minnesota
Karla Ballman	Division of Biostatistics	Mayo Clinic
Antar Bandyopadhyay	Institute for Mathematics and its Applications	University of Minnesota
Joseph Beyene	Population Health Sciences Research Institute	Hospital for Sick Children
Maury Bramson	School of Mathematics	University of Minnesota
Olga Brezhneva	Institute for Mathematics and its Applications	University of Minnesota
Michael Brimacombe	Department of Preventive Medicine	New Jersey Medical School of UMDNJ
Philippe Broet		Université de Paris XI (Paris-Sud)
Atul Butte		Children's Hospital Informatics Program
Enrico Capobianco		NONE
Uma Chandran	Department of Pathology Informatics	University of Pittsburgh
Meng Chen	Department of Statistics	University of Wisconsin-Madison
Yidong Chen	National Human Genome Research Institute	National Institutes of Health
Laura Chihara	Department of Mathematics	Carleton College
Timothy Church	Division of Environmental and Occupational Health	University of Minnesota
Donald Connelly	Laboratory Medicine and Pathology	University of Minnesota
Yan Cui	Department of Molecular Sciences	University of Tennessee
David Dahl	Department of Statistics and Biostatistics and Medical Information	University of Wisconsin-Madison
Deborah Dawson	Department of Preventive and Community Dentistry/Biostat	University of Iowa
Ann Dewitt	Department of Genomics	3M
Christian Domnisoru		University of St. Thomas
Shen Dong	Department of Chemical Engineering and Materials Science	University of Minnesota
Sandrine Dudoit	Division of Biostatistics	University of California, Berkeley
Donald Dunbar	Target Discovery	Organon Inc.
Anja Forche	Department of Genetics, Cell Biology and Development	University of Minnesota
Shmuel Friedland	Department of Mathematics, Statistics, and Computer Science	University of Illinois at Chicago
Patrick Gaffney	Department of Medicine	University of Minnesota
Tim Garoni	Institute for Mathematics and its Applications	University of Minnesota
Elizabeth Garrett	Division of Oncology Biostatistics	Johns Hopkins University
Constantine Gatsonis	Department of Biostatistics	Brown University
Balaji Gopalakrishnan	Institute for Mathematics and its Applications	University of Minnesota
Suzanne Grindle	Cancer Center, BioInformatics	University of Minnesota
Jennifer Hall	Department of Medicine	University of Minnesota
Chuan-Hsiang Han	Institute for Mathematics and its Applications	University of Minnesota
Leonid Hanin	Department of Mathematics	Idaho State University
Douglas Hawkins	School of Statistics	University of Minnesota
Robert Hebbel	Department of Medicine	University of Minnesota
Wolfgang Huber	Department for Molecular Genome Analysis	Deutsches Krebsforschungszentrum (Cancer Research)(DKFZ)
Marianne Huebner	Department of Statistics and Probability	Michigan State University
Fern Hunt	Mathematical and Computational Sciences Division	National Institute of Standards and Technology
Naresh Jain	School of Mathematics	University of Minnesota
Sonia Jain	Department of Biostatistics	University of California, San Diego
Yuan Ji	Department of Statistics	University of Wisconsin-Madison
Aixiang Jiang	Department of Medicine	University of Minnesota
Kisee Joo	Department of Mathematics	University of Kentucky
Rebecka Jornsten	Department of Statistics	Rutgers University
Lili Ju	Institute for Mathematics and its Applications	University of Minnesota
Mahrous Kandil	Department of Soil, Water, and Climate	University of Minnesota
Christina Kendziorski	Department of Biostatistics and Medical Informatic	University of Wisconsin-Madison
Kathleen Kerr	Department of Biostatistics	University of Washington
Mohammad Khan	Department of Mathematics	Kent State University
Boris Khots	Oil and Gas Division	Compressor Controls Corporation
Dohyun Kim	Department of Statistics	Seoul National University
Seongjai Kim	Department of Mathematics	University of Kentucky
Sek-Won Kong		Harvard Medical School
Thomas Kurtz	Department of Mathematics	University of Wisconsin-Madison
Pim Kuurman	Department of Animal Genomics	ID-Lelystad
Soumendra Lahiri	Department of Statistics	Iowa State University
Jeff Lande	Molecular, Cellular and Developmental Biology	University of Minnesota
Taerim Lee	Department of Information Statistics	Seoul National University
Hongzhe Li	Department of Statistics and Human Genetics	University of California, Davis
Wentian Li	Center for Genomics and Human Genetics	North Shore - LIJ Research Institute
Chihche Lin		University of Minnesota
Adriana Lopez		University of Pittsburgh
Jessica Lynch	Department of Neuroscience	University of Minnesota
Changqing Ma	Center for Pathology Informatics	University of Pittsburgh
Douglas Mahoney	Department of Biostatistics	Mayo Clinic
Richard McGehee	School of Mathematics	University of Minnesota
Geoff McLachlan	Department of Mathematics	University of Queensland
Mario Medvedovic	Department of Environmental Health	University of Cincinnati
Bruce Morlan	Cancer Center Statistics	Mayo Clinic
Peter Munson	Mathematical and Statistical Computing Laboratory	National Institutes of Health
Haewon Nam	Institute of Mathematics and Statistics	University of Minnesota
Michael Newton	Department of Statistics	University of Wisconsin-Madison
Amir Niknejad	Department of Mathematics	University of Illinois at Chicago
Ann Oberg	Department of Health Science Research	Mayo Clinic
Michael Ochs	Bioinformatics Facility	Fox Chase Cancer Center
Wei Pan	Division of Biostatistics	University of Minnesota
Peter Park	Department of Informatics	Children's Hospital Boston
Giovanni Parmigiani	The Sidney Kimmel Comprehensive Cancer Center	Johns Hopkins University
Lea Popovic	Institute for Mathematics and its Applications	University of Minnesota
John Quackenbush		The Institute for Genomic Research
Arvind Raghavan	Department of Microbiology	University of Minnesota
Marco Ramoni		Harvard Medical School
J. Rao	Department of Biostatistics and Epidemiology	Case Western Reserve University
Lidia Rejto	Department of Food and Recource Economics	University of Delaware
Grzegorz Rempala	Department of Mathematics	University of Louisville
David Rocke	Center for Image Processing and Integrated Comp.	University of California, Davis
Guilherme Rosa	Department of Animal Science	Michigan State University
James Rosenberger	Department of Statistics	Pennsylvania State University
Mauricio Salcedo	Laboratorio de Oncologia Genomica	Hospital de Oncologia
Fadil Santosa	Institute for Mathematics and its Applications	University of Minnesota
Arnd Scheel	School of Mathematics	University of Minnesota
Paola Sebastiani	Department of Mathematics & Statistics	University of Massachusetts
Mark Segal	Department of Epidemiology and Biostatistics	University of San Francisco
Sashirekha Shanmugavelu	Department of Computer Engineering	University of Minnesota
William Shannon	Division of General Medical Sciences	Washington University School of Medicine
Hae-Hiang Song	Department of Biostatistics	The Catholic University of Korea
Terence Speed	Department of Statistics	University of California, Berkeley
Jingran Sun		University of Minnesota
Mahlet Tadesse	Department of Statistics	Texas A & M University
Joachim Theilhaber	Cambridge Genomics Center	Aventis Pharmaceuticals, Inc.
Terry Therneau	Division of Biostatistics	Mayo Clinic
Achim Tresch	Department of Bioinformatics	Fraunhofer Institute
Mark van der Laan	Division of Biostatistics	University of California, Berkeley
Marina Vannucci	Department of Statistics	Texas A & M University
Jing Wang	Institute for Mathematics and its Applications	University of Minnesota
Lin Wang	Department of Microbial Engineering	University of Minnesota
Stephen Willson	Department of Mathematics	Iowa State University
Fred Wright	Department of Biostatistics	University of North Carolina
Guanghua Xiao		University of Minnesota
Yang Xie		University of Minnesota
Andrei Yakovlev	Center for Biostatistics and Computational Biology	University of Rochester
Jean Yang	Division of Biostatistics	University of San Francisco
Yuhong Yang	Department of Statistics	Iowa State University
Kenny Ye	Department of Applied Mathematics and Statistics	SUNY
Haoyu Yu	Department of Supercomputing Institute	University of Minnesota
Ming Yuan	Department of Statistics	University of Wisconsin-Madison
Ofer Zeitouni	School of Mathematics	University of Minnesota
Jun Zhao	Institute of Mathematics and its Application	University of Minnesota